ࡱ> + P) * @PBN( Q, M, M - N), and we want the loss to equal the revenue V on the margin. So, the break-even equation is:; ( V + P) * @PBN( Q, M, M - N) = V; ! Note, you should round up if M is fractional; END MODEL: ! This overbooking model determines the number of reservations, M, to allow on a flight if the no-show distribution is binomial; ! Some available data ; N = 16; ! Total seats available; V = 225; ! Revenue from a sold seat; P = 100; ! Penalty for a turned down customer; Q = .04; ! Probability a customer is a no-show; ! The probability to turn down customers is @PBN( Q, M, M - N), therefore the corresponding expected loss due to imperfect information is: ( V Root EntryCONTENTS Root Entry*0_^(e Contents  \cf1 @PBN\cf2 ( Q, M, M - N) = V; \par \par \cf3 ! Note, you should round up if M is fractional;\cf2 \par \par \cf1 END\cf2 \par \par } {\rtf1\ansi\ansicpg1252\deff0\deflang1033{\fonttbl{\f0\fnil\fcharset0 Courier New;}} {\colortbl ;\red0\green0\blue255;\red0\green0\blue0;\red0\green175\blue0;} \viewkind4\uc1\pard\cf1\f0\fs20 MODEL\cf2 : \par \cf3 ! \par This overbooking model determines the number of \par reservations, M, to allow on a flight if the \par no-show distribution is binomial;\cf2 \par \par \cf3 ! Some available data ;\cf2 \par N = 16; \cf3 ! Total seats available;\cf2 \par V = 225; \cf3 ! Revenue from a sold seat;\cf2 \par P = 100; \cf3 ! Penalty for a turned down customer;\cf2 \par Q = .04; \cf3 ! Probability a customer is a no-show;\cf2 \par \par \cf3 ! The probability to turn down customers is \par @PBN( Q, M, M - N), therefore the corresponding \par expected loss due to imperfect information is: \par ( V + P) * @PBN( Q, M, M - N), and we want the \par loss to equal the revenue V on the margin. So, \par the break-even equation is:;\cf2 \par \par ( V + P) *